nm000349 NEMAR-native dataset

Chamanzar2020: Ultra high-density EEG of interictal migraine and controls during visual, auditory stimulation and rest

Ultra high-density 128-channel EEG recorded from 18 individuals with migraine (interictal) and 21 healthy controls. Recordings include steady-state visual evoked potential (SSVEP) and steady-state auditory evoked potential (SSAEP) tasks at 4 and 6 Hz, as well as eyes-open resting state. The data support analyses of cortical coherence abnormalities in migraine.

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Issues GitHub

Download this dataset

Pick a method. Large datasets skip the zip and use the streaming methods below — all resumable. Full download guide →

  1. Download archive (.zip) — 23.9 GB

    A single zip of the published version. Best for small/medium datasets.

    Download zip

  2. NEMAR CLI recommended

    Pulls the pinned version + annexed data and resumes cleanly. Install nemar-cli →

    nemar dataset download nm000349
  3. DataLad

    Clone the dataset repo and fetch file content on demand. Docs →

    datalad clone https://github.com/nemarDatasets/nm000349 nm000349
    cd nm000349 && datalad get .
  4. git-annex

    Plain git + git-annex against the dataset repo. Docs →

    git clone https://github.com/nemarDatasets/nm000349 nm000349
    cd nm000349 && git annex get .
  5. Direct files (wget / curl / rclone)

    Every file with a stable, range-resumable URL from the manifest. Needs curl, jq, wget (or rclone/aria2c). Docs →

    curl -s https://data.nemar.org/nm000349/v1.0.0/manifest.json | jq -r '.[].bytes_url' > urls.txt
    wget -xc -i urls.txt

Compute on this dataset

Two routes today, with a third (in-browser one-click submission) landing soon.

  1. NeuroScience Gateway (NSG) portal.

    NSG runs EEGLAB / Brainstorm / MNE pipelines on supercomputing time donated by SDSC. Create an account, point a job at this dataset's S3 prefix (s3://nemar/nm000349), and submit.
    nsgportal.org →

  2. Local processing with nemar-cli.

    Pull the dataset to your machine and run any toolbox locally. Honors the published version pinning.

    npm install -g nemar-cli
    nemar dataset clone nm000349
    cd nm000349 && nemar dataset get
  3. Just the files.

    rclone, aria2c, or any HTTPS client works against data.nemar.org/nm000349/ — the manifest carries presigned S3 URLs.

Direct compute access is coming soon. One-click NSG submission from this page is scoped for a follow-up phase. Tracked on nemarOrg/website#6.

Citations

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    Files

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    Signal viewer

    How to use the data (for agentic research) license, citation, download commands

    What it is

    Modalities
    EEG
    Participants
    39
    Size
    26.8 GB
    Tasks
    rest, ssaep, ssvep

    License and terms

    License
    CC-BY-4.0
    Recommended citation
    Chamanzar, A., Haigh, S. M., Grover, P., & Behrmann, M. (2026). Chamanzar2020: Ultra high-density EEG of interictal migraine and controls during visual, auditory stimulation and rest (Version v1.0.0) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000349

    Where the bytes are

    Latest version (always current)
    https://data.nemar.org/nm000349/latest/

    How to download

    The dataset
    nemar dataset download nm000349 Clones and fetches in one step. Content under stimuli/ and derivatives/ is skipped by default because those trees can be large; add --stimuli --derivatives for the whole thing.
    A subset, one step
    nemar dataset download nm000349 --subjects sub-01,02 Also filters by --sessions, --tasks, --runs, --datatypes, --include and --exclude.
    A subset, step 1
    nemar dataset clone nm000349 Clones git-annex pointers only; fetches no file content. Creates ./nm000349.
    A subset, step 2
    cd nm000349 The get command below reads the clone's annex, so it only works from inside the clone.
    A subset, step 3
    nemar dataset get <files> Pulls the files you actually need. Skips stimuli/ and derivatives/ unless the path you ask for is under one of them.
    One small file
    https://data.nemar.org/nm000349/v1.0.0/participants.tsv A direct HTTPS fetch works for any single file.